Evaluation of Melanoma Thickness with Clinical Close-up and Dermoscopic Images Using a Convolutional Neural Network

Convolutional neural networks (CNNs) have shown promise in discriminating between invasive and in situ melanomas. The aim of this study was to analyse how a CNN model, integrating both clinical close-up and dermoscopic images, performed compared with 6 independent dermatologists. The secondary aim w...

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Detalles Bibliográficos
Autores principales: GILLSTEDT, Martin, MANNIUS, Ludwig, PAOLI, John, DAHLÉN GYLLENCREUTZ, Johan, FOUGELBERG, Julia, JOHANSSON BACKMAN, Eva, PAKKA, Jenna, ZAAR, Oscar, POLESIE, Sam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society for Publication of Acta Dermato-Venereologica 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9677275/
https://www.ncbi.nlm.nih.gov/pubmed/36172695
http://dx.doi.org/10.2340/actadv.v102.2681

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9677275/
https://www.ncbi.nlm.nih.gov/pubmed/36172695
http://dx.doi.org/10.2340/actadv.v102.2681

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